Robot Machine Learning Engineer

About Deft RoboticsOur mission is to build the world’s first labor agency that deploys dexterous robots as its primary workforce.We start by deploying wheeled humanoid robots in industrial manufacturing and assembly lines.You’ll be joining a team of extremely hardcore and self-motivated engineers, scientists, and operators who focus on winning 24/7.You will develop and own entire systems from design to deployment, playing a foundational role in deploying 5000+ robots by 2031.What you'll do Design and develop a modular robot autonomy stack that composes Vision-Language-Action (VLA) models with purpose-built modules to enable grasping and dexterous behaviors in unstructured environmentsDevelop action refinement and safety layers that post-process VLA outputs — constraint satisfaction, collision and force guards, smoothing, and runtime monitors for safety-critical deploymentArchitect clean interfaces and abstractions around base VLA models so they can be swapped, benchmarked, and upgraded as the SOTA evolves — keeping the stack model-agnostic  Design and maintain robust data collection and curation pipelines for production robot fleets Build reliable, high-speed robot autonomy software stack optimized for inference performance Advance SOTA dexterous manipulation architecture through novel methodologies while bridging theory & practice—real customer use-cases with clear success criteria.Required Qualifications PhD or MS degree in Computer Science, Machine Learning, Robotics, or equivalent technical disciplineDeep expertise in machine learning fundamentals, reinforcement learning, and associatedframeworks (PyTorch, TensorFlow, Ray, etc.)3+ years of proven track record developing and deploying ML systems from research through production implementationHands-on experience with model lifecycle management including training, deployment, and maintenance in production settingsPreferred Qualifications Authored or co-authored peer-reviewed publications in robotics or related fieldsHands-on experience designing and implementing bimanual manipulation tech stacks with imitation learning or RL-based methodsBackground in real-time ML inference systems, simulation-to-reality transfer, or advanced reinforcement learning implementationsBenefits We support publishing at top robotics/ML venues and presenting at conferences (travel + time fully covered). Medical, dental & vision plansDaily meals stipendHiring Process Phone screen + 2 virtual technical interviews + onsiteExpected Compensation $150,000 - $200,000 annual salary + cash and stock awards + benefitsThe pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.